Narrative Discourse in Aphasia: Main Concept and Core ...Core Lexicon Analyses of the Cinderella...

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Narrative Discourse in Aphasia: Main Concept andCore Lexicon Analyses of the Cinderella StoryEmily Patricia DillowUniversity of South Carolina - Columbia

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Narrative Discourse in Aphasia: Main Concept and Core Lexicon Analyses of the Cinderella Story

by

Emily Dillow

Bachelor of Arts University of South Carolina, 2011

______________________________________

Submitted in Partial Fulfillment of the Requirements

For the Degree of Master of Speech Pathology in

Speech Pathology

Arnold School of Public Health

University of South Carolina

2013

Accepted by:

Jessica D. Richardson, Director of Thesis

Hiram L. McDade, Reader

Lacy Ford, Vice Provost and Dean of Graduate Studies

ii

© Copyright by Emily Dillow, 2013 All Rights Reserved.

iii

Dedication

To my parents for getting me started on my journey towards thesis completion by

emphasizing education and encouraging persistence from an early age. In the words of

Randy Pausch, “I won the parent lottery.” I cannot thank you enough for all the early

literacy exposure that set me up for success in life. If every child in America had the

upbringing I did, so many more potentials would be reached and ambitions would be

realized.

iv

Acknowledgments

First, I would like to thank those who fostered my initial interest in speech-

pathology in general, and research, in particular. Thank you, Dr. Crass, for teaching a

fantastic introductory speech pathology course, which can truly be described as the seed

of my passion for the study of communication disorders. Many professors have

influenced the clinician and researcher I have become, and I am grateful for every one of

them. I would like to specifically thank Dr. den Ouden for the role he played in inspiring

me to pursue research, as professor of my wonderful research course.

Thank you, Dr. Richardson and Dr. McDade, for contributing your valuable time

as members of my committee to make my goal possible. Thank you, especially, Dr.

Richardson, for not only agreeing to be my thesis director, but for projecting enthusiasm

from the get-go. Your passion for improving the lives of individuals with aphasia has

made working on this project so meaningful and enjoyable. I appreciate every minute you

have put into mentoring me and I will be forever grateful for my first amazing laboratory

experience. In the words of Eleanor Roosevelt, “A good leader inspires people to have

confidence in the leader, a great leader inspires people to have confidence in themselves.”

Dr. Richardson is, without a doubt, a great leader.

Finally, thank you to my labmates for being the most positive, hilarious, and

motivating labmates anyone could ask for.

v

Abstract

Discourse is a highly individualized and complex speech act essential for

effective communication in daily life. Individuals with language disorders demonstrate

impaired narrative ability and a resultant decline in functional communication (Webster,

Franklin, & Howard, 2007). Discourse analysis is often time-consuming and impractical

for everyday clinical use. Most informative discourse measures require specialized

training to perform and are time-consuming. A clinically practical measurement is

lacking. Standardized core lexicon and main concept lists for discourse tasks could

potentially allow clinicians to efficiently assess discourse skills and predict activity and

participation limitations. This study presents the development and application of a core

lexicon and main concept list for monologic narration of the Cinderella story (utilizing

AphasiaBank). Analyses were conducted on the following groups: controls, anomic,

Broca’s, conduction, Wernicke’s.

Results indicated that both analyses clearly separated individuals with aphasia

from those with typical language abilities. Both analyses were able to distinguish some

subtypes of aphasia but were unable to differentiate each subtype from one another.

Importantly, core lexicon analysis correlated strongly with the more time intensive

measure of main concept analysis for all groups. Results of this study lend support to the

usefulness of further development and application of core lexicon and main concept

analyses as efficient methods of determining narrative adequacy in PWAs.

vi

Table of Contents

Dedication……………………………………………………………………………...…iii

Acknowledgments………………………………………………………………………..iv

Abstract…………………………………………………………………………………....v

List of Tables…………………………………………………………………………….vii

List of Figures…………………………………………………………………………...viii

Chapter 1: Introduction……………………………………………………………………1 Chapter 2: Methods…………………………………………………………………...….10 Database……………………………………………………………………….....10 Materials…………………………………………………………………………11 Procedure…………………………………………………………………...........11 Statistical Analysis……………………………………………………………….14 Chapter 3: Results……………………………………………………………………..…17 Chapter 4: Discussion……………………………………………………………………28 References……………………………………………………………………………..…39 Appendix A: Cinderella Core Verb Lexicon………………………………………….…43 Appendix B: Cinderella Core Noun Lexicon…………………………………………….44 Appendix C: Cinderella Main Concepts………………………………………………....45

vii

List of Tables

Table 3.1 Subtypes vs. Controls: Entire Lexicon.………………………………….........20

Table 3.2 Subtypes vs. Controls: Core Verbs.…………………………………….……..20

Table 3.3 Subtypes vs. Controls: Core Nouns...…………………………………………20

Table 3.4 Subtype Comparisons: Entire Core Lexicon.…………………………………21

Table 3.5 Subtype Comparisons: Core Verbs…………….……………………….….…21

Table 3.6 Subtype Comparisons: Core Nouns…...…………………………………..…..22

Table 3.7 Subtypes vs. Controls: Main Concept Score….……………………...……….22

Table 3.8 Subtype Comparisons: Main Concept Score.……………………….……...…23

Table 3.9 Relationship Between Main Concepts and Core Lexicon………………….…23

viii

List of Figures

Figure 3.1 Core Lexicon Production…...…………………………………………...……24

Figure 3.2 Core Verb Production……...………………………………………...……….24

Figure 3.3 Core Noun Production…………...………………………………………...…25

Figure 3.4 Main Concept Scores.…………………………...…………………………....25

Figure 3.5 Relationship Between Main Concepts and Core Lexicon……………………26

Figure 3.6 Relationship Between Main Concepts and Core Verbs…………………...…26

Figure 3.7 Relationship Between Main Concepts and Core Nouns…….……………..…27

1

CHAPTER 1

Introduction

Due to productivity requirements and pressure from insurance companies, speech-

language pathologists must utilize the most time-efficient methods of assessing initial

impairments and measuring progress during treatment. Along with being time-efficient, it

is imperative that assessment tools are actually providing an indication of a patient’s

functional communication skills. MacWhinney, Fromm, Holland, Forbes, and Wright

(2010) suggest that comparing a patient’s noun and verb lexicon during a specific

narrative task to a created core lexicon may be a time-efficient and informative

assessment method. Core lexicons can be developed by analyzing transcripts of non-brain

injured individuals with the help of tools, such as Computerized Language Analysis

(CLAN). Grande et al. (2008) concluded that computer analysis of specific discourse

measurements (e.g., percentage open class words, mean length of utterance, syntactic

complexity) could be a practicable tool for use in clinical settings. Their study found that

not only was the analysis of basic parameters efficient, but also that the measurements

obtained were more sensitive to changes over the course of treatment than more

commonly used rating scales (i.e., Aachen Aphasia Test). While it should be noted that

the authors suggested further research is needed to determine the specificity of these

basic parameters, the fact that computer analysis of basic parameters appeared more

sensitive to improvement than rating measurements certainly warrants attention. A

measurement, such as percentage of core words produced, could potentially provide an

2

efficient and meaningful indication of narrative discourse skill and improvement over the

course of treatment. Because core lexicons would be based on narratives of non-brain

injured individuals, production of a greater number of core words would suggest a

narrative is more similar to that of typical speakers. Webster, Franklin, and Howard

(2007) emphasize the importance of performing extensive discourse analysis on control

subjects in order to have a relevant measure of comparison when analyzing the discourse

of persons with aphasia (PWAs). Without basing standards on actual productions of

control participants, there is no way of assuring relevancy.

Much of the research in the area of word retrieval involves assessment during

confrontation naming tasks (Mayer & Murray, 2003). Some studies have demonstrated a

relationship between word retrieval during confrontation naming and word retrieval

during conversation, suggesting that improved word retrieval during confrontation

naming results in similarly improved word retrieval during conversation (Brown &

Cullinan, 1981; Hickin, Best, Herbert, Howard, & Osborne, 2001). However, other

studies have failed to demonstrate a relationship between the two and emphasize the fact

that confrontation naming is quite different from real-word speaking situations. Berndt,

Haendiges, Burton, and Mitchum (2002) found that PWAs had much more difficulty with

sentence completion tasks than confrontation naming. Meanwhile, Mayer and Murray

(2003) found that confrontation naming was a more difficult task for PWAs when

compared to picture description or discourse. Together, these studies provide support for

the idea that performance on one speech-language production task cannot predict the

performance on another. Edwards (1998) clearly demonstrated this variability in deficits

of PWAs over a variety of tasks, suggesting that several different types of tasks must be

3

used to get a full picture of a PWA’s abilities. Given this information, most clinicians

would agree that narrative tasks should be included for a thorough sample of

communication.

Questions arise about what type of task should be used to elicit this narrative

sample. Previous research suggests that different narrative tasks do, indeed, facilitate

different levels of output quality and quality for both PWAs and control speakers

(Fergadiotis & Wright, 2011; Fergadiotis, Wright, & Capilouto, 2011). Some different

narrative tasks which have been used in research and clinical settings include procedural

accounts of common activities, picture description, story generation using a series of

pictures, story retell without pictures, and narration of a personal event (Fergadiotis &

Wright, 2011; Fergadiotis et al., 2011). Each of these tasks provides different levels of

support for semantic retrieval (Fergadiotis & Wright, 2011; Fergadiotis et al., 2011).

Personal narrative tasks, for example, provide the most freedom and least support, which

may seem optimal when trying to assess functional communication. However, several

practical concerns arise when considering the use of personal narrative tasks, the primary

concern being that because clinicians are unfamiliar with all personal events in each of

their client’s lives, they may be unable to judge the correctness of a personal narrative. In

addition, relying solely on the use of personal narratives would eliminate the possibility

of developing a standardized core lexicon for efficient and standardized performance

assessment.

Although discourse tasks, such as story narration, are thought to provide valuable

information to clinicians, they are underused due to practical concerns of time and

training (Armstrong, Brady, Mackenzie, & Norrie, 2007; Boles & Bombard, 1998;

4

Olness, Gyger, & Thomas, 2012). Thorough discourse analysis requires lengthy samples

of speech, which can be time-consuming in clinical settings (Boles & Bombard, 1998).

However, a study by Boles and Bombard (1998) found that even discourse samples as

short as five minutes can provide reliable information regarding discourse skill, as long as

the particular behavior of interest occurs at least three times per minute. Since core words

occur much more frequently than three per minute, one short story may very well provide

enough information for reliable assessment.

Along with obtaining a lengthy narrative sample, another concern is the amount

of time and training required for phonetic transcription and error coding (Armstrong et

al., 2007) in order to precisely record every word, including details such as paraphasias,

repetitions, and revisions, which characterize the speech of PWAs. Armstrong (2007)

reported that one researcher suggested that one minute of speech could take close to an

hour to transcribe, while another researcher reported that even when using computerized

software, one minute of speech takes about 10 minutes to perform accurate phonetic

transcription. In light of these time demands, Armstrong (2007) expresses the need for

non-transcription-based analysis in order to make narrative assessments feasible in

clinical settings. With a core lexicon analysis, a clinician would simply need to record a

certain class of words while listening to their patient’s narration of one story and later

compare the words produced to the core lexicon list.

The current study focused on monologic narration of a familiar story. This type of

task is confining enough to provide listeners with sufficient context and allow for

standardized measurement. Meanwhile, it is not so restrictive as to prevent valid

assessment of functional communication (Webster et al., 2007). The monologic narration

5

task was selected over a procedural task or picture descriptions that have been shown to

elicit less lexical diversity (Fergadiotis & Wright, 2011; Fergadiotis et al., 2011). Further,

monologic narrative tasks have been shown to elicit greater lexical diversity in control

speakers and illustrate disparities in output between PWAs and control speakers that may

not be apparent based on a short picture description task (Fergadiotis & Wright, 2011).

We selected the Cinderella story, a task commonly used for narrative assessment in

PWAs (MacWhinney et al., 2010; MacWhinney, Fromm, Forbes, & Holland, 2011; Bird

& Franklin, 1996; Webster et al., 2007). Bird and Franklin (1996) discussed the clinical

use of the Cinderella story as a means of measuring impairments and improvements of

PWAs. Cinderella is a story familiar to the general population and is of adequate length

to elicit sufficient output.

Speech production deficits are known to differ between the different aphasia

subtypes, suggesting that it may be necessary to analyze narrative skills of subtypes

separately. In Grande et al.’s (2008) study involving computerized analysis of discourse,

the parameters most sensitive to improvements in participants with fluent aphasia

differed from the parameters most sensitive to improvements in participants with non-

fluent aphasia. In light of this information, it may be the case that a core lexicon list is

more predictive of narrative adequacy for one subtype of aphasia, but less relevant for

another subtype. Due to this possibility, the current study looked at the different subtypes

of aphasia separately. It was decided that even grouping by fluent and non-fluent aphasias

would allow too much variability within groups, since the broad categories of fluent and

non-fluent aphasia each encompass a number of different subtypes with different speech

patterns. Therefore, the subgroups of anomic, Broca’s, conduction, and Wernicke’s were

6

each analyzed separately. Because limited sample sizes were available for the subtypes of

transcortical motor, transcortical sensory, and global aphasia, these subtypes were not

included in the analysis. However, it may be expected that individuals with transcortical

motor aphasia would perform similarly to our Broca’s subjects and individuals with

transcortical sensory aphasia would perform similarly to our Wernicke’s subjects.

Meanwhile, the deficits present in individuals with global aphasia make core lexicon

analysis an inappropriate assessment method due to the paucity of output.

Analyzing an entire lexicon, even just for one narrative task, does not seem to be

the most efficient usage of a core lexicon approach to assessing narrative skill. This

would be too time-intensive and may not provide specific information that may be

offered by a more narrow analysis. Creating core lexicons of specific lexical classes

allows us to see the predictive capabilities of lexical class usage independent of one

another, as well as in combination. In the current study, core lexicon lists were created for

the lexical classes of verbs, nouns, and adjectives, which are the classes that carry the

bulk of semantic information. A study by Berndt et al. (2002) provided support for the

countless researchers who have noted production deficits along lexical class lines. The

study looked at whether imageability can explain patterns of production, which have been

thought to be caused by the effects of lexical class. Results showed that there were

deficits specific to nouns or verbs, which were not simply due to imageability. This

possibility of potential lexical class deficits warrants investigation using separate target

lexicon lists for verbs, nouns, and adjectives.

When comparing different types of aphasia, numerous studies have found that

PWAs with agrammatic speech have greater difficulty with verbs, while individuals with

7

fluent aphasia have greater difficulty with nouns (Armstrong, 2001; Bird, Howard,

Franklin, 2003; Gordon, 2008; Luzzatti et al., 2002; Thompson, Lukic, King, Mesulam,

& Weintraub, 2012). Gordon (2008) explains that PWAs with agrammatic speech have

greater difficulty with verbs due to the fact that verbs have more syntactic weight than

nouns. Because individuals with agrammatic speech have a deficit in syntax that those

with fluent aphasia do not, agrammatic speakers are the ones who show a stronger verb

deficit. However, not every study follows this pattern. Some studies have, in fact,

reported verb impairments in non-agrammatic PWAs (Druks, 2002; Thompson et al.,

2012). By separating analyses of verbs, noun, and adjective core lexicons, as well as

separating the different classes of aphasia, in the current study we are able to observe

whether lexical class deficits exist and how they may differ between subtypes of aphasia.

Based on the previous literature, it was predicted that in the current study, subjects with

Broca’s aphasia would produce disproportionately fewer core verbs and adjectives than

core nouns. Subjects with anomic, conduction, and Wernicke’s aphasia were predicted to

exhibit greater impairment in producing core nouns and adjectives, as compared to core

verbs. While other parts of speech could provide additional information about narrative

adequacy, it was decided to only look at the chosen three lexical classes in order to

maintain the quick nature of the tool. Verbs, nouns, and adjectives are the three largest

categories of open-class words, and they carry the majority of meaning in discourse.

Since the goal was to develop a tool to assess the amount of information individuals were

able to express, it was felt that analysis of these three lexical classes would provide

sufficient information.

8

One limitation of a core lexicon analysis is that it does not assess the contextual

use of the core words. In order to be considered a clinically applicable tool for the

assessment of narrative adequacy, core lexicon production must be shown to correlate

with established measurements of narrative adequacy. Main concept analysis is a

narrative measure supported by previous studies as being an informative method of

assessing adequacy of communication (Nicholas & Brookshire, 1995; Kong, 2009). Main

concept analysis is not only sensitive to differences in information content, but it is also a

reliable measure when obtained by numerous evaluators (Nicholas & Brookshire, 1995).

Beyond providing information regarding ability during a specific narrative task, an

increase in the number of main concepts produced was shown to be significantly

correlated with listeners’ ratings of functional communication improvement (Ross &

Wertz, 1999). While it would be ideal to have information on how appropriately PWAs

are able to use the words in context, the process of obtaining such information detracts

from the efficiency. However, if core lexicon measures were to correlate highly with

main concept measures, then the former could prove to be an efficient assessment tool

that could predict functional communication ability and chart change in those abilities.

The current study began with the development of a core lexicon for the Cinderella

story. This lexicon was generated based on monologic narration by control participants

and was originally intended to include verbs, nouns, and adjectives. Because only one

adjective was produced by enough participants to be considered core, it was decided to

exclude the sole adjective and have the core lexicon be comprised entirely of nouns and

verbs. The total number of core verbs and nouns produced by each control and each

person with aphasia (anomic, Broca’s, conduction, and Wernicke’s) was determined.

9

Core lexicon productions of each subtype were compared to that of controls and to every

other subtype. A main concept list was also established based on control transcripts. With

the established list, Cinderella narratives of all control participants and persons with

anomic, Broca’s, conduction, and Wernicke’s were coded and scored. Scores were added

up for calculation of a main concept composite score for each participant. Main

composite scores of each subtype were compared to controls and to every other subtype.

Finally, core lexicon production was correlated to main concept composite score for

controls and each of the four aphasia subtypes. Core verb production and core noun

production were also separated correlated to main concept composite score for each of

the five groups.

For the current study, it was predicted that core lexicon production would

correlate significantly to main concept production, and that the correlation would be

stronger when investigating the correlation with the entire core lexicon than with just

verbs or nouns. It may be the case that these correlations differ for the aphasia subtypes,

but it was predicted that similar correlations would exist when looking at subjects with

different types of aphasia.

10

CHAPTER 2

Methods

Database

This study utilized AphasiaBank, an online database of multimedia resources

available for researchers and clinicians involved in the study and treatment of PWAs.

Along with providing demographic information and assessment scores of all subjects, the

database also includes videos and transcripts of subjects completing a variety of tasks,

including Cinderella story narration. One hundred fifty-eight non-aphasic control subjects

from the AphasiaBank database were used for the creation of a core lexicon for the

Cinderella story. A smaller sample of control transcripts (N = 51) were included in the

development of a main concept list than in the establishment of a core lexicon, simply

due to the fact that main concept analysis is a much more time intensive process. In order

to ensure that the main concepts would be reflective of a typical adult of any age, the

same numbers of control transcripts (N = 17) were analyzed from three age groups (20 -

40, 41 - 60, 61 - 80). In order to decrease risk of any bias of age or gender, during the

selection of controls, subjects in each of the three age groups were matched for gender

and age within each range. One hundred thirteen PWAs of four aphasia subtypes were

included in the analyses of core lexicons and main concepts. The total numbers of

participants separated by aphasia type were as follows: 45 anomic, 30 Broca’s, 25

conduction, and 13 Wernicke’s. Individuals with transcortical motor, transcortical

11

sensory, and global aphasia were not included due to the small number of these types

existing on AphasiaBank (range of one to five transcripts). Subjects without a Cinderella

transcript were also excluded from the study.

Materials

Cinderella story transcripts, of both PWAs and control subjects, were retrieved

from the AphasiaBank database. Computerized Language Analysis (CLAN) was used to

formulate lists of all the verbs and nouns produced by control subjects, along with the

number of subjects producing each word (incidence). After establishing core lexicon and

main concept lists with the use of Excel, CLAN was again utilized to generate

spreadsheets with the verbs, nouns, and adjectives produced by each PWA. SPSS

software was used to perform statistical analysis of the compiled data.

Procedure

Aim 1: Investigating Core Lexicon

Core verb, noun, and adjective lexicons were created for the Cinderella story,

based on the narratives of all control subjects on AphasiaBank (N = 158). Core verb and

core noun lists have been created for the Cinderella story in a previous study

(McWhinney et. al. 2010) based on 25 subjects. All verbs, nouns, and adjectives

produced by at least 20% of subjects were included in the core lexicon lists. The current

study included a larger group of control subjects (N = 158), and in order to be included in

the core lexicon list, a word had to be produced by at least 50% of subjects. Fifty percent

was selected due to the fact that it yielded a reasonably sized lexicon and has served as a

criterion in previous language research, such as in Brown’s stages of language

development (Owens, 2008). The inclusion criterion of 50% generated core lexicon lists

12

that reflect the elements that seem to be essential to successful narration of the Cinderella

story. The more stringent criterion resulted in only one adjective meeting the

qualification. Therefore, adjectives were not included in the analyses, as originally

intended. Once the lexicons were established, the numbers of core nouns and verbs

produced by each PWA (N = 113) and by each control (N = 158) were counted, and each

subtype was compared to controls. To determine how well each method of analysis was

able to differentially characterize the four subtypes of aphasia, the subtypes were first

compared on the number of core lexical items produced (nouns and verbs) and then a

closer examination of potential differences between nouns and verbs followed.

Aim 2: Investigating Main Concepts

Control transcripts were also analyzed in order to establish a list of main concepts,

again using the inclusion criterion of 50% production. All relevant concepts were

identified in each of 51 control transcripts. A relevant concept was defined as a correct

utterance about the Cinderella story that contained a subject, one main verb, and an

object, if appropriate. It could also contain subordinate clauses, as long as it contained

only one main verb (Nicholas & Brookshire, 1995). A master list of all relevant concepts

produced was developed, in which relevant concepts were simplified to the form of

subject, verb, and object for ease of comparison across participant. Any relevant concepts

that were judged to have the same basic message were regarded as the same concept to

allow for varying vocabulary (e.g., “his family decided it was time for him to take a

wife,” “the young prince is at a point where he needs to select a bride to get married to

carry on the lineage of the royal family”, and “once there was a prince who was looking

for a princess,” were judged to cover the same main concept of “the prince needed to find

13

a wife”). The frequency of occurrence of concepts was recorded across all subjects, and

any concept spoken by 50% or more of subjects was listed as a main concept. Using the

created main concept list, each transcript (51 controls, 113 PWAs) was scored according

to a scoring system we adapted from Nicholas and Brookshire (1992), which included the

following codes: inaccurate incomplete, inaccurate complete, accurate incomplete, and

accurate and complete. Every transcript received the same number of codes, one for each

concept on the master list of main concepts. In order to be coded as accurate, a statement

had to include no incorrect information. A single semantic paraphasia would result in a

statement being coded as inaccurate, because this meets the definition of incorrect

information. Statements including phonemic paraphasias, however, could be coded as

accurate as long as the phonemic error does not cause any ambiguity with the regards to

intended word production. Completeness was determined by whether every component

deemed to be a necessary concept of a main concept was mentioned in the speaker’s

production. Based on these definitions of accuracy and completeness, accurate and

complete concepts had to contain all components of the main concept with no incorrect

information. Accurate, but incomplete concepts contained no incorrect information, but

left out a component of the main concept. Inaccurate, yet complete statements contained

at least one incorrect piece of information, but mentioned all components of the

established main concept. Lastly, the coding of inaccurate and incomplete was given

when a statement clearly corresponded with a main concept, but included at least one

incorrect component and failed to include at least one component of the main concept.

After being coded based on accuracy and completeness, corresponding scores were

assigned, and a composite score for each subject was computed. Statements coded as

14

absent received a score of zero, statements coded as inaccurate and incomplete received a

score of one, statements coded as inaccurate but complete or accurate but incomplete

received scores of two, and statements coded as accurate and complete received scores of

three. The PWAs, and then each subtype separately, were compared to controls based on

main concept composite score. To determine how well each method of analysis was able

to differentially characterize the four subtypes of aphasia, the subtypes were compared

based on main concept composite score.

Aim 3: Relationship Between Core Lexicon and Main Concepts

Correlations were determined between the number of core words produced and

main concept scores for controls and each aphasia subtype separately. Further analyses

were conducted to look at relationships between core nouns and main concept scores and

core verbs and main concept scores for controls and each subtype.

Statistical Analysis


A median test was conducted comparing the entire core lexicon production of

PWAs to that of controls. Non-parametric tests were used throughout the analyses due to

skewed distributions of data. The median test was selected, as opposed to the Mann

Whitney U Test, because distributions were not homogeneous across groups. Four

median tests were conducted in order to compare each subtype (anomic, Broca’s,

conduction, Wernicke’s) to controls based on core lexicon production. Alpha levels for

these tests were determined based on the Holm-Bonferroni method of correction from an

original alpha level of .05 in order to decrease the likelihood of type I error. After

comparing each subtype to controls based on core lexicon, two more families of tests

15

were run using the aforementioned procedure to compare specifically the core verb and

noun productions of the four subtypes to those of controls. To determine whether any

differences existed in core lexicon productions across the four subtypes of aphasia,

another median test was conducted. Controls were not included in this comparison in

order to prevent the resulting magnitude of difference from being inflated by the much

higher core lexicon production of controls. For each family of tests, alpha levels were

adjusted using the Holm-Bonferroni method.


A median test was conducted comparing main concept composite score of PWAs

and controls. Four median tests, with alpha levels adjusted by Holm-Bonferroni

correction, were then conducted comparing each subtype individually to controls. Next, a

median test was conducted to determine whether differences existed between main

concept scores across the four subtypes. Finally, median tests were conducted to compare

each subtype to each of the other subtypes based on main concept composite score. As

with previous analyses, alpha levels were adjusted using the Holm-Bonferroni method for

each family of tests.


A Spearman’s correlation coefficient was computed on the relationship between

core lexicon production and main concept composite scores across all groups.

Spearman’s correlation coefficients were computed, as opposed to Pearson correlation

coefficients, because data was not normally distributed. Spearman’s correlation

coefficients were also calculated between each of the two individual lexical class

productions (verb and noun) and main concept scores. Fifteen more correlation

16

coefficients were computed in order to obtain the same information for the control,

anomic, Broca’s, conduction, and Wernicke’s groups, separately. For every correlation

coefficient obtained, a significance test was also conducted.

17

CHAPTER 3

Results


The established core lexicon consisted of 26 verbs and 19 nouns (Appendix A and

Appendix B). The median core lexicon production of controls was 32.5, while the median

for PWAs was 12. A median test evaluating the difference between core lexicon

production in controls and PWAs was significant, χ2 (1, n = 271) = 127.788, p < .001,

with a large Cramer’s V of .687. Median tests comparing core lexicon production for

each of the subtypes individually to controls were all significant, with effect sizes ranging

from .282 to .426 (Table 3.1). All median tests comparing specifically the number of core

verbs and nouns produced by the subtypes of aphasia to the numbers produced by

controls were also significant, with effect sizes ranging from small to somewhat large

(Tables 3.2 and 3.3).

Once establishing the difference between PWAs and controls, the difference

between subtypes was then explored. A median test indicated a significant difference

between groups, χ2 (3, n = 113) = 27.279, p <. 001 with a Cramer’s V of .491. When

further tests were conducted comparing every possible pair of subtypes, Broca’s was the

only subtype whose core lexicon production significantly differed from any of the others

(Table 3.4), differing significantly from both the anomic and conduction groups, but not

from the Wernicke’s group. Three of the six median tests subsequently conducted on core

verb productions of each pair of subtypes revealed significant differences (Table 3.5).

18

The significant differences in core verb production between Broca’s and anomic groups

and Broca’s and Wernicke’s groups both had large effect sizes (.512 and .503), while the

significant difference in core verb production between anomic and conduction groups had

a medium effect size (.346). The three pairs showing no significant difference in core

verb production were anomic and Wernicke’s, conduction and Wernicke’s, and

conduction and Broca’s (Table 3.5). Comparisons of individual subtypes revealed

significant differences between four of the six pairs of subtypes (Table 3.6). Differences

between core noun production of the anomic and Broca’s groups and the conduction and

Broca’s group were particularly strong, with effect sizes of .533 and .559, respectively

(Table 3.6). The pairs that were not differentiated by core noun production alone were

anomic and conduction and Broca’s and Wernicke’s (Table 3.6).


During the development of a main concept list, 28 concepts met the 50%

inclusion criterion and were included as main concepts (Appendix C). Median main

concept composite scores were as follows: 63 for controls, 25 for anomic, 8.5 for

Broca’s, 12 for conduction, and 7 for Wernicke’s (Figure 3.4). A median test comparing

main concept scores of all PWAs to controls was significant, χ2 (1, n = 164) = 64.547, p <

.001, with a large effect size of .627. All median tests comparing individual subtypes to

controls were also significant, with large effect sizes ranging from .505 to .758 (Table

3.7). A subsequent median test comparing main concept production of the four subtypes

of aphasia indicated a significant difference, as well, χ2 (3, n = 113) = 21.867, p < .001,

with an effect size of .440. Two of the six median tests conducted between each pair of

subtypes were significant (Table 3.9) – the anomic subtype produced significantly more

19

main concepts than Broca’s and conduction subtypes. Boxplots of main concept scores of

all five groups can be found in Figure 3.4.


Spearman correlations indicated significant relationships between main concept

score and core lexicon production for all groups (Table 3.9). A strong positive correlation

existed between the two variables for all groups (Figure 3.5). Correlations between main

concept score and core verb production were slightly weaker, but still significant for all

groups, except Wernicke’s, r (11) = .468, p = .106 (Table 3.9, Figure 3.6). Correlations

between main concept score and core noun production were also weaker than the

correlations involving the entire core lexicon. However, these correlations were still

significant for all groups (Table 3.9, Figure 3.7).

20

Table 3.1

Subtype vs. Controls: Entire Lexicon

Groups Chi-squared P-Value Cramer’s V

Anomic vs. Controls* 36.802 < .001* .426

Broca’s vs. Conduction* 28.832 < .001* .392

Conduction vs. Controls* 24.568 < .001* .366

Wernicke’s vs. Controls* 13.584 < .001* .282 *significant at adjusted alpha level following Holm-Bonferroni correction

(original alpha of .05)

Table 3.2

Subtype vs. Controls: Core Verbs






(original alpha of .05) Table 3.3

Subtype vs. Controls: Core Nouns




Conduction vs. Controls* 4.778 .029* .162

Wernicke’s vs. Controls* 9.289 .002* .233 *significant at adjusted alpha level following Holm-Bonferroni correction


21

Table 3.4

Subtype comparisons: Entire Core Lexicon


Anomic vs. Broca’s* 27.009 < .001* .600

Anomic vs. Conduction 3.579 .059 .226

Anomic vs. Wernicke’s .892 .345 .124


Broca’s vs. Wernicke’s 5.736 .017 .365

Conduction vs. Wernicke’s .012 .899 .021 *significant at adjusted alpha level following Holm-Bonferroni correction


Table 3.5

Subtype Comparisons: Core Verbs


Anomic vs. Broca’s* 19.667 < .001* .512

Anomic vs. Conduction* 8.359 .004* .346

Anomic vs. Wernicke’s .646 .421 .106

Broca’s vs. Conduction .120 .729 .047

Broca’s vs. Wernicke’s* 10.896 .001* .503

Conduction vs. Wernicke’s 1.117 .290 .171 *significant at adjusted alpha level following Holm-Bonferroni correction


22

Table 3.6

Subtype Comparisons: Core Nouns


Anomic vs. Broca’s* 21.346 < .001* .533

Anomic vs. Conduction 1.556 .212 .149

Anomic vs. Wernicke’s* 7.259 .007* .354


Broca’s vs. Wernicke’s 1.100 .294 .160

Conduction vs. Wernicke’s* 6.886 .009* .426 *significant at adjusted alpha level following Holm-Bonferroni correction


Table 3.7

Subtype vs. Controls: Main Concept Score







23

Table 3.8

Subtype Comparisons: Main Concept Scores


Anomic vs. Broca’s* 15.705 < .001* .458

Anomic vs. Conduction* 8.359 .004* .346

Anomic vs. Wernicke’s 4.858 .028 .289

Broca’s vs. Conduction 2.183 .140 .199

Broca’s vs. Wernicke’s .054 .817 .035

Conduction vs. Wernicke’s 2.184 .139 .240 *significant at adjusted alpha level following Holm-Bonferroni correction


Table 3.9

Relationship Between Main Concepts and Core Lexicon

Groups MCs & Core Lexicon

MCs & Core Verbs

MCs & Core Nouns

All Groups (162)

.925, < .001* .878, < .001* .850, < .001*

Controls (49)

.771, < .001* .725, < .001* .621, < .001*

Anomic (43)

.894, < .001* .790, < .001* .851, <.001*

Broca’s (28)

.755, < .001* .648, < .001* .725, < .001*

Conduction (23)

.851, < .001* .798, < .001* .592, .002*

Wernicke’s (11)

.693, .009* .468, .106 .859, < .001*

*significant at adjusted alpha level following Holm-Bonferroni correction (original alpha of .05) Note. In column one, degrees of freedom are listed in parentheses. In

columns two through four, the first number listed is Spearman’s rank

correlation coefficient, and the second number listed is the p-value.

24

Figure 3.1. Core Lexicon Production.

Figure 3.2. Core Verb Production.

25

Figure 3.3. Core Noun Production.

Figure 3.4. Main Concepts.

26

Figure 3.5. Relationship Between Main Concepts and Core Lexicon.

R2 listed in parentheses; R2 across all groups=.856.

Figure 3.6. Relationship Between Main Concepts and Core Verbs.

R2 listed in parentheses; R2 across all groups=.771.

27

Figure 3.7. Relationship Between Main Concepts and Core Nouns. R2 listed in parentheses; R2 across all groups=.723.

28

CHAPTER 4

Discussion


MacWhinney et al. (2010) suggested core lexicon analysis during narration may

provide a time-efficient and informative indication of functional communication. For

example, clinicians would not need to perform lengthy transcription, but instead could

generate a list of words spoken during narration for later comparison to a core lexicon.

What is needed is a core lexicon derived from a large sample of controls, ensuring that

the lexicon reflects typical discourse abilities. After analyzing transcripts of 158 adults

with typical language and utilizing a more stringent criterion of 50% incidence, the

resultant core lexicon reflects what is essential to successful Cinderella narration. This

core lexicon list can be utilized by clinicians in the previously described manner as a tool

for narrative discourse assessment.

Comparison of the core lexicon production of controls and PWAs indicated

markedly greater production by controls. While this result was expected, establishing this

difference was a necessary initial step in core lexicon analysis. Results of the three

median tests comparing core lexicon, verb, and noun productions of the four subtypes

suggest that distinctions in core verb and noun production are evident between aphasia

subtypes. This information may have important implications for the validity of core

lexicon analysis, as it suggests that this measure may be sensitive to differences between

aphasia subtypes. When specifically comparing pairs of subtypes based on entire core

29

lexicon production, Broca’s was the only subtype that could be differentiated from others.

This suggests that core lexicon analysis may not be sensitive enough to differences

between the other subtypes.

The same findings do not hold true when looking specifically at individual lexical

class productions. While just looking at core verbs would be sufficient for differentiating

Broca’s from anomic and Wernicke’s subtypes, this information would not be adequate

for differentiating Broca’s from conduction. Based on findings from this study, analysis

of core verb and noun productions would be necessary in order to make the distinction

between Broca’s and conduction. Another interesting finding regarding core verb

comparisons was that anomic and conduction subtypes were differentiated on this

measure, even though this was not the case based on entire lexicon comparisons.

Meanwhile, core noun analysis could sufficiently make distinctions between all pairs,

except anomic and conduction and Broca’s and Wernicke’s subtypes. After comparing

groups based on the entire core lexicon and individual classes, it is clear that the different

measures result in varying degrees of discrimination between different pairs of aphasia

subtypes.


Standardized main concept lists for discourse tasks could allow clinicians to

efficiently assess discourse skills and predict activity and participation limitations. The

generated main concept list could potentially serve as a clinically useful checklist for

narrative assessment of individuals with aphasia when the Cinderella narrative is elicited

according to AphasiaBank conventions. Similarly to the procedure with core lexicon

analysis, an important initial step in the exploration of main concept analysis was to

30

ensure its ability to highlight a clear difference between discourse skill of PWAs and

controls. The strong effect sizes of all tests comparing the different subtypes of aphasia to

controls based on main concept scores indicate that we can be confident in this measures’

ability to detect language impairment.

The median test comparing the four subtypes’ main concept scores suggested

that the measure was also able to distinguish subtypes within subjects with aphasia.

However, further median tests comparing each set of pairs indicated that anomic aphasia

was the only subtype significantly different from any of the others with regard to main

concept scores. Main concept scores of Broca’s, conduction, and Wernicke’s subtypes

were too similar to suggest any difference between these three subtypes.

It is interesting to note that while the median main concept score of 25 for the

anomic group was significantly higher than that of the Broca’s and conduction subtypes,

it was still significantly lower than the median score of 63, obtained by controls. While

anomic aphasia is primarily characterized as a word-finding disorder, Andreetta,

Cantagallo, and Marini (2012) suggested that narrative coherence can also be impacted in

this population. Deficits in discourse skills may be so minor with this population that they

are not apparent on many standardized assessment measures, but it should not be

assumed that they do not exist and do not affect functional communication abilities. The

notable gap apparent between main concept scores of controls and subjects with anomic

aphasia makes main concept analysis a promising tool for detecting discourse weaknesses

in anomic aphasia.

31


The relationship between core lexicon production and main concept scores was

investigated to determine whether the quick core lexicon analysis correlated strongly with

the more thorough (but time-intensive) analysis of narrative discourse. Main concept

analysis is a narrative measure which has been supported by previous studies as being a

reliable and informative method of assessing adequacy of communication (Nicholas &

Brookshire, 1995; Kong, 2009). Our results suggest core lexicon production is strongly

related to main concept scores for all groups (controls and all subtypes of aphasia), which

makes it a promising method of assessment. This finding lends support to the idea that

core lexicon analysis may be a comparable and time-efficient method of characterizing

discourse abilities and, potentially, charting treatment outcomes.

Tests of whether core verbs or core nouns alone correlated with main concept

scores of each group indicated that individual lexical classes due, indeed, correlate

significantly with main concept productions, except in one particular case. For the

Wernicke’s group, core verb productions did not correlate significantly with main

concept scores. Meanwhile, the number of core nouns produced showed a stronger

correlation to main concept scores than did total core lexicon production (Table 3.9).

These results indicate a notable gap between the noun and verb usage of individual’s with

Wernicke’s aphasia (e.g. “and the two girls, they go to this meeting,” contains 1 core verb

“go,” but the participants fails to get credit for “stepsisters” or “ball” because of non-

specific noun usage.). This information is useful and suggests that if a clinician were to

use the core verb production of a patient with Wernicke’s aphasia to estimate their likely

main concept score, the clinician could be overestimating the patient’s actual abilities in

32

the area of main concept production. In fact, core noun analysis specifically would be

more appropriate than core lexicon analysis for individuals with Wernicke’s aphasia,

based on results of correlational tests in this study. For all other groups, the best method

of predicting main concept score would be core lexicon analysis, including both verbs

and nouns. The only other subtype exhibiting a noticeable difference between

correlations obtained with core verbs versus core nouns was the conduction group.

Unlike the Wernicke’s group, which seemed to show a greater deficit with nouns, the

conduction group seemed to show a greater deficit with verbs. However, this tendency

was not strong enough to prevent the combined measurement of verb and noun

production from being the stronger measurement of discourse skill, based on correlations

to main concept scores.

Further Discussion

Time-efficiency was a primary motivator for pursuing core lexicon and main

concept analyses as methods of assessment. While the CLAN system has yet to be

automated with these assessment functions, relative efficiency exists even in the manual

calculation of these measurements. While the completion of this study required much

deliberate analysis, the most time-consuming portions related to the creation of the core

lexicon and main concept lists, and not in the subsequent use of the tools. Core lexicon

analysis, in particular, was a quick method of acquiring a quantitative measurement.

Commands can be inserted into CLAN with desired specifications. For core lexicon

analysis, one can request the program to create an excel spreadsheet of all the verbs or all

the nouns a participant produced specifically during narration of one story. The assessor

can then highlight the columns corresponding to words included in the core lexicon and

33

count the total number produced by the participant. Once the core lexicon tool is created

within CLAN, even this short process will be eliminated, and simply typing in the core

words produced by a client will provide immediate results. Main concept analysis

required substantially more time than core lexicon analysis, and, admittedly, may be an

unrealistic tool for clinical use until automization occurs. Judging accuracy and

completeness of concepts requires careful consideration, and it is hoped that through the

input of many variations and alternative productions into CLAN, the system will be able

to code concepts accordingly.

Along with being time-efficient, the other main concern regarding these

assessment tools was that the information they provided actually indicate relevant skills.

The fact that we are in need of discourse analysis tools that reflect functional

communication and life participation make the task of establishing relevancy difficult.

We were not able to correlate our findings to an established standardized assessment tool

with strong psychometric properties, but several points can be made, which suggest

promise for the relevancy of these analyses. First, and foremost, core lexicon, core verb,

core noun, and main concept analyses all clearly separated speakers with and without

aphasia. Secondly, some logical results arose from these analyses, such as higher

production scores for anomic participants and lower production scores for Broca’s

participants. Lastly, the fact that core lexicon and main concept analyses were

significantly correlated for every subtype, and strongly so for most subtypes, serves as

somewhat of a validity check for the two measurements. The tools are designed to assess

narrative ability, they follow distinctly different methods, and, yet, they result in highly

correlated findings. In order to truly determine whether core lexicon and main concept

34

analysis are valid assessments for determining life participation and functional

communication ability, future studies will need to gather quantitative data for these

targeted outcomes. A study currently in progress within this lab involves investigating the

validity of core lexicon and main concept analysis as predictors of listener perceptions of

a speaker by correlating the scores of speaker to listener ratings of the speaker. Other

future studies could correlate the discourse analysis scores to results of questionnaires

completed by speakers themselves and by family members in order to determine how

they really relate to the measurements that matter, functional communication and life

participation.

Grande et al. (2008) found computer analysis of discourse measurements to be

sensitive enough to monitor improvement over the course of treatment. Because the

current study looked only at a single narrative sample of each participant, nothing can be

drawn from the data about the longitudinal abilities of core lexicon and main concept

analyses. Future research is needed, in which several narrative samples are collected and

analyzed at different times throughout the course of intervention.

Webster et al. (2007) stated the importance of first analyzing transcripts of control

subjects to get a clear picture of how a person without language impairment would

produce a story. This suggestion was followed in the current study to ensure that the core

lexicon and main concept lists reflected typical Cinderella narrative productions. The

production of PWAs was simply compared to that of adults of a similar age range, who,

as a group, were in no way more familiar with the task than the PWAs themselves. This

method of developing core lexicon and main concept lists based on control participants is

suggested for future studies, as opposed to having researchers generate lists based on

35

their own, perhaps biased, notions. Establishing core lexicons and main concepts for a

wide variety of tasks and a large number of prompts would allow clinicians to assess

skills for different communication needs and allow them to repeatedly assess progress

without the concern of improved performance simply due to familiarity with the prompt.

Another study currently in progress in this lab is developing a main concept list for a

sequencing task, as well as for a picture description task.

As suggested by Edwards (1998), no one task should be used to assess the speech

and language abilities of a client. Although, core lexicon and main concept analyses

could contribute to a well-rounded assessment, this is not to say that they should be used

in place of established aphasia assessment tools. These analyses should, instead, be tools

for use in conjunction with other measurements as a way of gaining additional

information not attained otherwise.

After analyzing 271 Cinderella transcripts, further support can be added to the

claim that the Cinderella story is ideal for a narrative task. The story was familiar to most,

predictable enough for researchers to interpret productions, and demanding enough to

require a lengthy and complex narrative. There was notable variability in the way

different narrators worded the same concepts, so it will be vital to develop methods of

recognizing such variable productions when creating the automatized program within

CLAN. A study currently in progress in this lab is investigating differences in the main

concepts produced during narration of the Cinderella story based on age. This could have

important implications for which main concepts and how many main concepts you should

expect a client to produce. Perhaps distinct main concept lists are warranted for different

36

age ranges. If this is the case, follow-up studies will explore the need for separate core

lexicon lists based on age, as well.

Core lexicon and main concept scores were reflective of speech production

differences between some subtypes, but were unable to differentiate each and every

subtype from one another. Grande et al.’s (2008) found that the best tools for showing

improvements of a speaker with one type of aphasia may not be the same as those most

sensitive to improvements made by a speaker with another type of aphasia. The current

study supported this finding in that core nouns are more strongly correlated to main

concept score in those with Wernicke’s aphasia, but core verbs are more strongly

correlated to main concept score in those with Conduction aphasia. Other differences can

be seen between groups in the tables and figures of results.

Core lexicon production correlated strongly to main concept scores for all

subtypes, despite the fact that the core lexicon established for this study included only

two lexicon classes. This provides evidence that analyzing only verb and noun production

is not only a time saving strategy, but it is also a technique that provides sufficient

information for judgment of narrative quality. Because time is a finite commodity and a

single client can only be allocated a certain amount of a clinician’s time, assessments

should only be as long as deemed necessary for obtaining relevant information. Seeing as

core lexicon production correlated strongly to main concept production while only

consisting of verbs and nouns, spending time analyzing other lexicon classes would likely

not provide enough additional information to be justifiable, though should be ruled in or

out with further research. Interesting, based on results of this study, analyzing noun

production alone, rather than noun and verb production, may actually provide a better

37

indication of narrative quality for individuals with Wernicke’s aphasia. Looking at nouns

and verbs is most informative for all other subtypes. However, if time is extremely

limited, verb production is most informative of speakers with conduction aphasia and

noun production is most informative of those with anomic and Broca’s aphasia.

Analyzing the suggested lexical classes for each subtype provides a slightly weakened

prediction of main concept production as compared to analyzing the two class lexicon

together. While there may be a situation in which a clinician opts for single lexical class

analysis, analyzing both verbs and nouns seems to be the most optimal and efficient use

of time for clients with all subtypes of aphasia, except Wernicke’s.

Future Research

A potentially informative follow-up study of this particular data would be to

further investigate the differences in main concept production between aphasia subtypes,

by comparing the accuracy and completeness codes received by each subtype. This study

judged main concept production only based on composite score, which may be leaving

out pertinent information regarding production. Perhaps, for example, certain subtypes

lost the majority of points in the area of accuracy, while another subtype lost the majority

of points in the area of completeness. This information would be helpful to know. The

developed core lexicon and main concept lists will be utilized in other investigations of

speakers with aphasia and of other populations, such as TBI. The effects of gender and

age on the quantitative and qualitative aspects of discourse will be explored using the

generated main concept list. If clear differences existed, several lists could be developed,

allowing clinicians to determine discourse adequacy using a list that is most appropriate

to a given client's demographics. As more subjects are added to AphasiaBank, and to the

38

newly developed TBIBank, lexicons and main concepts will be re-analyzed, and the lists

will be revised. Perhaps a future study could include other lexical classes, such as

pronouns and conjunctions, to investigate whether their inclusion may strengthen the

method’s predictive power or provide some information regarding coherence. Main

concept and core lexicon lists could also be developed for other discourse tasks, such as

picture description and sequencing. To establish functional relevance of these two

discourse measurements, future studies should investigate their correlations to quality of

life measures and to listener ratings of narrative adequacy. Along with making checklists

immediately available, another future direction of this research is to develop automatized

core lexicon and main concept analyses tools within Computerized Language Analysis

(CLAN). It is essential that researchers continue to develop time-efficient methods of

discourse analysis to equip clinicians and researchers with practicable tools for measuring

functional outcomes.

Conclusion

Discourse analysis is often time-consuming and impractical for everyday clinical

use. Results of this study lend support to the usefulness of further development and

application of core lexicon and main concept analyses as efficient methods of

determining narrative adequacy in PWAs. With these tools, the goal is that clinicians will

increasingly target narrative discourse during treatment of PWAs. Long-term, it is hoped

that an increased emphasis on discourse will result in greater quality of life for PWAs.

39

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43

APPDENDIX A: Cinderella Core Verb Lexicon

Be

Come

Could

Dance

Do

Find

Fit

Get

Go

Have

Know

Leave

Live

Look

Lose

Make

Marry

Run

Say

See

Take

Tell

Try

Turn

Want

Will

44

APPENDIX B: Cinderella Core Noun Lexicon

Ball

Cinderella

Daughter

Dress

Fairy

Foot

Girl

Glass

Home

Horse

House

Midnight

Mother

Mouse

Prince

Pumpkin

Sister

Slipper

Time

45

APPENDIX C: Cinderella Main Concepts

• Dad got remarried.

• Stepsister and/or stepmother were mean to Cinderella.

• Cinderella sweeps/cleans/does all the housework.

• The prince needs to find a wife.

• There is going to be a ball.

• They (or anyone in the house) got an invitation [to the ball].

• Cinderella isn’t allowed to go.

• Cinderella obtains (finds/makes) a dress.

• Stepsisters ruin/tear/throw away/take her dress.

• Cinderella was upset/crying.

• Along came her fairy godmother.

• Fairy godmother turned pumpkin and mice into carriage and horses.

• Fairy godmother made a beautiful gown and pretty glass slippers.

• Cinderella went to the ball/dance/party.

• Cinderella has to be home by midnight.

• Prince and Cinderella dance.

• Prince falls in love/is enamored with Cinderella.

• The clock struck midnight/She realizes she must leave.

• She ran for the stairs/ran for the door.

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• Prince falls in love/is enamored with Cinderella.

• The clock struck midnight/She realizes she must leave.

• She ran for the stairs/ran for the door.

• She gets away/gets to the carriage/gets home.

• She lost (left, dropped) one of the glass slippers/slipper was left.

• The prince (or his servants) uses slipper to search for Cinderella.

• The prince and/or his servants showed up at Cinderella’s house.

• Two stepsisters try the slipper on.

• The slipper didn’t fit the stepsisters.

• The slipper fit Cinderella.

• Cinderella and the prince get married.

• Cinderella and the prince lived happily ever after.

Narrative Discourse in Aphasia: Main Concept and Core ...Core Lexicon Analyses of the Cinderella...

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